Learning on your own sucks, so we won’t do that to you. Each course will have a cohort of students working through the content together — watch lectures at your own pace, and join, and will mix together self-led lectures with synchronous tutorials (the flipped-classroom model, for any education buffs out there!)
You’ll use relevant datasets, real tools, and learn to solve problems experienced by data teams every day. No iris or titanic datasets, and no web-based IDEs.
Taught by experts
Search for the term “analytics engineer”, and it won’t take you long to find content written by our founding team, Michael Kaminsky and Claire Carroll. Between the two of us we’ve:
- Been members of data team
- Run data teams
- Built leading data communities
- Mentored dozens of analytics engineers
- Trained hundreds of analytics engineers
- Written technical content used by thousands of people every month
So it’s safe to say — we know what we’re talking about.
Meet the instructors
As the sole analyst at a fast-growing startup, Claire experienced the pain of the traditional analyst workflow — an ever-growing backlog of requests, and numbers that never quite matched up. So she taught herself dbt, the command line, version control and brought all the rigor of analytics engineering to her team.
After realizing the impact that an analytics engineering mindset could have on an analyst’s career, Claire took on a role growing the dbt community, bringing analytics engineering to thousands of data analysts and engineers.
Michael has worked as an economist, statistician, analyst, data scientist, but analytics engineering will always hold a special place in his heart. Michael built one of the world’s first analytics engineering teams while leading the data team at online-razor-startup-turned-CPG-goliath Harry’s and has written extensively about the practice as a founding leader of the Locally Optimistic blog and community.
Join our mailing list, and we’ll let you know when applications open.
Part time — we expect that students will spend around 5 hours a week completing coursework.
Before starting the course, you should already know how to write SQL to answer business questions (for example, reporting monthly revenue) and have some exposure to business intelligence tools. That’s it!
We’ll have a full curriculum available soon. As a baseline, expect to learn about the command line, version control, dbt, advanced SQL patterns, and orchestrators.
That’s not a question! But that is something we’re interested in. Drop us an email, and we’ll get in touch.
Recent blog articles we’ve written
Data education is broken